Related Experiment Video
Updated: Jun 26, 2026
12:50
Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds
Published on: September 26, 2017
Measuring the accuracy of agro-environmental indicators
David Makowski1, Muriel Tichit, Laurence Guichard
1INRA, UMR 211, INRA AgroParisTech, BP 01, 78850 Thiverval-Grignon, France. makowski@grignon.inra.fr
Journal of Environmental Management
|January 9, 2009
Summary
Agro-environmental indicators vary widely in accuracy for assessing farming impacts. Plant characteristics like crop yield offer the most reliable data for evaluating environmental policies and practices.
Area of Science:
- Agricultural Science
- Environmental Science
- Ecology
Background:
- Agronomists and ecologists have developed numerous agro-environmental indicators over 20 years.
- These indicators aim to assess farming's environmental impact and monitor agro-environmental policies.
Purpose of the Study:
- To measure the accuracy of various agro-environmental indicators using experimental data.
- To evaluate the utility of information sources (farmer practices, plant/soil data) used by indicators.
Main Methods:
- Considered four indicator series: grassland bird habitat quality, oilseed rape disease risk, nitrogen fertilizer pollution risk, and weed infestation.
- Utilized multiple datasets from cultivated plots and grasslands to assess indicator accuracy.
- Estimated indicator sensitivity, specificity, and probability of correctly ranking plots.
Main Results:
- Agro-environmental indicators demonstrated widely varying accuracy, with some performing poorly.
- Certain indicators showed informative value and better-than-random discriminatory ability.
- Indicators incorporating plant characteristics (e.g., grass height, disease incidence, crop yield) performed best.
Conclusions:
- The accuracy of agro-environmental indicators is highly variable, necessitating careful selection.
- Plant-based data provides more reliable insights for assessing environmental impacts compared to practice-based data.
- The developed statistical method aids researchers, advisors, and policymakers in comparing indicator performance.
Related Concept Videos
01:52Accuracy and Precision
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. Highly accurate measurements...
01:52Accuracy and Precision
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. Highly accurate measurements...
03:37Uncertainty in Measurement: Accuracy and Precision
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value.
01:11Statistical Analysis: Overview
When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
02:35Key Elements for Plant Nutrition
Like all living organisms, plants require organic and inorganic nutrients to survive, reproduce, grow and maintain homeostasis. To identify nutrients that are essential for plant functioning, researchers have leveraged a technique called hydroponics. In hydroponic culture systems, plants are grown—without soil—in water-based solutions containing nutrients. At least 17 nutrients have been identified as essential elements required by plants. Plants acquire these elements from the atmosphere, the...